diff --git a/main.py b/main.py
index e49ba54..34d76b6 100644
--- a/main.py
+++ b/main.py
@@ -113,20 +113,20 @@ if __name__ == "__main__":
     device_flag = torch.cuda.current_device() if torch.cuda.is_available() else -1
 
     query_rewriter = pipeline("text2text-generation", model="castorini/t5-base-canard")
-    intent_classifier = pipeline("sentiment-analysis", model='/models/intent_classifier', device=device_flag)
-    entity_extractor = spacy.load("/models/entity_extractor")
-    offensive_classifier = pipeline("sentiment-analysis", model='/models/offensive_classifier', device=device_flag)
-    ambig_classifier = pipeline("sentiment-analysis", model='/models/ambig_classifier', device=device_flag)
+    intent_classifier = pipeline("sentiment-analysis", model='/app/models/intent_classifier', device=device_flag)
+    entity_extractor = spacy.load("/app/models/entity_extractor")
+    offensive_classifier = pipeline("sentiment-analysis", model='/app/models/offensive_classifier', device=device_flag)
+    ambig_classifier = pipeline("sentiment-analysis", model='/app/models/ambig_classifier', device=device_flag)
     coref_resolver = spacy.load("en_coreference_web_trf")
         
     nlu = NLU(query_rewriter, coref_resolver, intent_classifier, offensive_classifier, entity_extractor, ambig_classifier)
 
     #load retriever and generator
-    retriever = SentenceTransformer('/models/BigRetriever/').to(device)
-    qa_generator = pipeline("text2text-generation", model="/models/train_qa", device=device_flag)
-    summ_generator = pipeline("text2text-generation", model="/models/train_summ", device=device_flag)
-    chat_generator = pipeline("text2text-generation", model="/models/train_chat", device=device_flag)
-    amb_generator = pipeline("text2text-generation", model="/models/train_amb_gen", device=device_flag)
+    retriever = SentenceTransformer('/app/models/BigRetriever/').to(device)
+    qa_generator = pipeline("text2text-generation", model="/app/models/train_qa", device=device_flag)
+    summ_generator = pipeline("text2text-generation", model="/app/models/train_summ", device=device_flag)
+    chat_generator = pipeline("text2text-generation", model="/app/models/train_chat", device=device_flag)
+    amb_generator = pipeline("text2text-generation", model="/app/models/train_amb_gen", device=device_flag)
     generators = {'qa': qa_generator,
                   'chat': chat_generator,
                   'amb': amb_generator,